Website Education Analytics
Education Analytics strives to deliver sophisticated, research-informed analytics to educators and school administrators to support their work in improving student outcomes. The Data Engineering team at EA supports them by ensuring that the data they receive is accurate, up to date, secure, and easily accessible. The person in this role will be a critical team member who helps to make that a reality.
We are seeking a full-time Data Engineer or Analytics Engineer to join our Data Engineering team. The person in this role will lead the design, build, and maintenance of automated data pipelines and analytic systems. An ideal candidate has strong SQL skills and experience with data warehousing concepts, familiarity with complex data integration and/or analysis, and an interest in improving K-12 education. The Data Engineering team covers extract/load processes as well as data warehouse design and transformations. While we want all our team members to have familiarity with all aspects of ELT, we welcome specialists who may be more experienced on either the data engineering or analytics engineering side.
This role supports the timely delivery of data and analytics to educators and administrators who use this data to drive change and improvement in education. We are looking for candidates who are innovative, hard-working, and curious to help us continue to develop our team’s capacity in the development and use of cutting-edge tools. Our team is consistently evaluating tools for new projects and looking for the best tools for the job. Our current stack uses an ELT approach via Apache Airflow and dbt to create data warehouses in Snowflake or Postgres, depending on the scale of the data. These posts illustrate some projects that members of our team might work on:
- Introducing Enable Data Union, an open framework for analytics and data warehousing with Ed-Fi data
- Check out our website for more about enable data union
Turning public data into custom insights: How EA has built a public data platform for our partners
- Building a multi-source analytics database to support teachers during COVID-19
- Lead the design and implementation of data warehousing structures for research, analytics, and reporting/dashboarding.
- Apply best practices from software engineering to data pipelines.
- Help implement code testing, continuous integration, and deployment strategies to ensure system reliability.
- Design and implement complex pipelines to integrate data coming from a mix of APIs, flat files, or other database sources.
- Develop and improve internal tools and systems to efficiently deliver high-quality, actionable metrics.
- Work collaboratively within a team of analysts, school system leaders, and other engineers to create analytics solutions that are scalable, easy to maintain, and support high quality research.
- Explore and apply new cutting-edge tools to drive innovation across a variety of projects.
- Experience architecting data warehouse and data lake structures that are intuitive and performant.
- Knowledge of best design practices in modern cloud-based data warehouses.
- Experience designing, implementing, and maintaining modern ELT pipelines with a clean codebase.
- Fluency in SQL, experience with Python and Linux.
- Knowledge of software engineering best practices, particularly in team-based development using Git.
- Ability to proactively identify and defend against potential data quality & processing issues.
- Experience with cloud-based columnar data warehouses (Snowflake, RedShift, BigQuery)
- Experience with Data Build Tool (dbt)
- Experience with Apache Airflow, or other modern data pipeline systems
- Familiarity with AWS tooling and best practices
- Desire to work with cutting edge tools in a fast-paced environment
How you will successfully onboard in this role
- First 30 days: Work through organizational and team onboarding. Get situated into Data Engineering team meetings and one on ones with your manager. Complete a training exercise our team has developed that familiarizes our new hires with our development setup and tooling.
- First 60 days: Begin to get involved in your first projects, familiarizing yourself with the project history, context, and goals by joining project meetings and connecting with teammates. Continue familiarizing yourself with our team’s workflow processes and tools.
- First 90 days: Now fully integrated into your first projects, making regular code and documentation contributions. You may start sharing your development at our team meetings. We will start planning for you to take a lead role on sub-tasks within a project.
- Hiring team reviews resumes, cover letters, and application question responses.
- Selected candidates are invited to a 30-minute interview with the hiring manager and a Senior Data Engineer to discuss skills, experience alignment, and interests.
- Selected candidates are sent a technical skills exercise. Hiring team reviews exercise submissions.
- Selected candidates are invited for a full day final interview (virtual or in person in our downtown Madison office). There will be another approximately 2-3 hours of interviews to meet other Data Engineering team members and key members of other teams and to help candidates learn more about Education Analytics & the role.
- Competitive salary 9 annual paid holidays, 26.5 days of paid vacation per year, and paid sick time
- 12% employer 401k contribution + 3% match
- Generous health and dental benefits
- Paid parental leave benefit of up to 26 weeks
- Subsidized office parking (for in person employees)
- Casual office environment
- Location right in the heart of downtown Madison, WI
The weekly expectation is 45 hours per week, and nights and weekends are sometimes required. Our preference is for candidates to primarily work from EA’s office in Madison, WI. We are open to hiring a remote team member for the right candidate.
Education Analytics is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Tell us about the interview process for this job
Hiring process 1. Hiring team reviews resumes, cover letters, and application question responses. 2. Selected candidates are invited to a 30-minute interview with the hiring manager and a Senior Data Engineer to discuss skills, experience alignment, and interests. 3. Selected candidates are sent a technical skills exercise. Hiring team reviews exercise submissions. Selected candidates are invited for a full day final interview (virtual or in person in our downtown Madison office). There will be another approximately 2-3 hours of interviews to meet other Data Engineering team members and key members of other teams and to help candidates learn more about Education Analytics & the role.
Tell us about your diversity and inclusion efforts
EA seeks to create a diverse team that reflects the people we serve. EA understands that diversity does not automatically facilitate inclusion, meaning that the organization actively works to promote a welcoming environment and foster a sense of belonging for staff of all identities through its policies and programs. EA seeks to eliminate disparities to industry entry and performance for those wishing to use their talents and skill in service to our mission. We recognize that staff enter with differing needs and that a workplace structured with difference in mind better serves all.
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To apply for this job please visit education-analytics.breezy.hr.